Toxicity of ionic liquids: Database and prediction via quantitative structure-activity relationship method

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	Toxicity of ionic liquids: Database and prediction via quantitative structure-activity relationship method
	Zhao, Yongsheng 1,2; Zhao, Jihong 2; Huang, Ying 1; Zhou, Qing 1; Zhang, Xiangping 1; Zhang, Suojiang 1
刊名	JOURNAL OF HAZARDOUS MATERIALS
	2014-08-15
卷号	278 期号:AUG.页码:320-329
关键词	QSAR Multiple linear regression (MLR) Support vector machine (SVM) Toxicity Ionic liquids
ISSN号	0304-3894
其他题名	J. Hazard. Mater.
中文摘要	A comprehensive database on toxicity of ionic liquids (ILs) is established. The database includes over 4000 pieces of data. Based on the database, the relationship between IL's structure and its toxicity has been analyzed qualitatively. Furthermore, Quantitative Structure Activity relationships (QSAR) model is conducted to predict the toxicities (EC50 values) of various ILs toward the Leukemia rat cell line IPC-81. Four parameters selected by the heuristic method (HM) are used to perform the studies of multiple linear regression (MLR) and support vector machine (SVM). The squared correlation coefficient (R-2) and the root mean square error (RMSE) of training sets by two QSAR models are 0.918 and 0.959, 0.258 and 0.179, respectively. The prediction R-2 and RMSE of QSAR test sets by MLR model are 0.892 and 0.329, by SVM model are 0.958 and 0.234, respectively. The nonlinear model developed by SVM algorithm is much outperformed MLR, which indicates that SVM model is more reliable in the prediction of toxicity of ILs. This study shows that increasing the relative number of O atoms of molecules leads to decrease in the toxicity of ILs. (C) 2014 Elsevier B.V. All rights reserved.
英文摘要	A comprehensive database on toxicity of ionic liquids (ILs) is established. The database includes over 4000 pieces of data. Based on the database, the relationship between IL's structure and its toxicity has been analyzed qualitatively. Furthermore, Quantitative Structure Activity relationships (QSAR) model is conducted to predict the toxicities (EC50 values) of various ILs toward the Leukemia rat cell line IPC-81. Four parameters selected by the heuristic method (HM) are used to perform the studies of multiple linear regression (MLR) and support vector machine (SVM). The squared correlation coefficient (R-2) and the root mean square error (RMSE) of training sets by two QSAR models are 0.918 and 0.959, 0.258 and 0.179, respectively. The prediction R-2 and RMSE of QSAR test sets by MLR model are 0.892 and 0.329, by SVM model are 0.958 and 0.234, respectively. The nonlinear model developed by SVM algorithm is much outperformed MLR, which indicates that SVM model is more reliable in the prediction of toxicity of ILs. This study shows that increasing the relative number of O atoms of molecules leads to decrease in the toxicity of ILs. (C) 2014 Elsevier B.V. All rights reserved.
WOS标题词	Science & Technology ; Technology ; Life Sciences & Biomedicine
类目[WOS]	Engineering, Environmental ; Engineering, Civil ; Environmental Sciences
研究领域[WOS]	Engineering ; Environmental Sciences & Ecology
关键词[WOS]	STRUCTURE-PROPERTY RELATIONSHIP ; SUPPORT VECTOR MACHINES ; PHYSICAL-PROPERTIES ; VIBRIO-FISCHERI ; PHYSICOCHEMICAL PROPERTIES ; QSPR CORRELATION ; NEURAL-NETWORKS ; MELTING-POINTS ; DAPHNIA-MAGNA ; CELL-LINE
收录类别	SCI
原文出处	://WOS:000340689100038
语种	英语
WOS记录号	WOS:000340689100038
公开日期	2014-09-30
内容类型	期刊论文
版本	出版稿
源URL	[http://ir.ipe.ac.cn/handle/122111/11628]
专题	过程工程研究所_研究所（批量导入）
作者单位	1.Chinese Acad Sci, Inst Proc Engn, Beijing Key Lab Ion Liquids Clean Proc, State Key Lab Multiphase Complex Syst, Beijing 100190, Peoples R China 2.Zhengzhou Univ Light Ind, Sch Mat & Chem Engn, Zhengzhou 450001, Peoples R China
推荐引用方式 GB/T 7714	Zhao, Yongsheng,Zhao, Jihong,Huang, Ying,et al. Toxicity of ionic liquids: Database and prediction via quantitative structure-activity relationship method[J]. JOURNAL OF HAZARDOUS MATERIALS,2014,278(AUG.):320-329.
APA	Zhao, Yongsheng,Zhao, Jihong,Huang, Ying,Zhou, Qing,Zhang, Xiangping,&Zhang, Suojiang.(2014).Toxicity of ionic liquids: Database and prediction via quantitative structure-activity relationship method.JOURNAL OF HAZARDOUS MATERIALS,278(AUG.),320-329.
MLA	Zhao, Yongsheng,et al."Toxicity of ionic liquids: Database and prediction via quantitative structure-activity relationship method".JOURNAL OF HAZARDOUS MATERIALS 278.AUG.(2014):320-329.